[WARNING! - Students should use alcohol thermometers, not mercury thermometers.
Also, students should be cautioned that thermometers can break and sharp
glass can cause cuts.]

Description:
Have you ever wanted to be able to perceive things others could not? Or
felt something magical when given a way to see something you are not normally
able to see? That is what remote sensing does for us. Each person is equipped
with remote sensors. We can see, hear, or sense the temperature of something
that we are not touching. Any device or sense that perceives an object without
contact is a remote sensor. Remote sensing instruments collect data that we do
not have the faculties to sense. They perceive, measure and record, energy in
the electromagnetic spectrum. Numbers and, in the case or remotely sensed
imagery (RSI), colors are assigned to represent frequencies in the range
perceived by the sensor.

Many remote sensors are sensitive to energy reflected in the infrared region of
the spectrum. Other instruments are sensitive to the visible and ultraviolet
regions of the spectrum. When sunlight strikes an object, part of the energy
is absorbed and other parts are reflected in wavelengths of varying lengths.
Waves reflected in the visible light band our eyes perceive as colors.

The waves that have a higher energy and are shorter than what we can see are
ultraviolet (and beyond) wavelengths. (See the diagram of the electromagnetic
spectrum in the lesson.)

The sensors used in remote sensing often operate at great distances from the
subject being measured. When we sense at close range the temperature of an
object, we are perceiving the temperature of the wavelengths that the object is
emitting. Remote sensing instruments that are sensitive to infrared
wavelengths detect these frequencies that the object reflects or did not
absorb.

An object that is cooler than surrounding objects is not emitting as much
infrared radiation (heat) as those other objects. For example, we perceive
forests as places that are cooler than areas that are developed and paved with
asphalt. A remote sensing instrument, registers less heat from the forest than
it does from the nearby road or suburb. Therefore it records a lower
temperature over a forest than over a downtown.

Once data are collected by the sensor, colors are assigned to the bands along
the range of wavelengths recorded. From this, digital images are produced.
Since the color of the objects is not true to what we are used to seeing, they
are called false-color images.. Any color can be assigned to a given frequency
to enhance specific features if desired.

This activity is done best on sunny days during the heat of the day. Return
with your students to the sight of the activity entitled,
Analog vs. Digital
and use thermometers to record the temperature of the ground in the center of
each square in the grid. Create a color guide coded to specific temperature
ranges to color the grid thereby creating a remotely sensed image.

Procedure:

Look at the aerial and satellite remotely sensed photographs from
Project ADEPT
. The LANDSAT imagery shows how remote sensing provides
information different from images taken with visible light.

Dambos are areas along riverbanks that absorb and hold stagnant water after
heavy rains. Disease carrying mosquitoes breed in this stagnant water. The
RSI shows in red the location of flooded dambos. (It may be noted that certain
radar systems enhance the capability of remote sensing by looking through
clouds, something that is not possible to do with aerial photography.)

Discuss with the students the background of the photos. What does the aerial
photo show us? What features can you see in the remotely sensed photo? When
would we need to use each type of image?

Ask students what remote sensor they used to collect data for the
activities in
Analog vs. Digital
(answer: their eyes). Today they will use
another remote sensor, a thermometer, which measures in a part of the spectrum
that humans can not see, in the infrared or what humans perceive as the heat or
thermal part of the spectrum.

Move the class to the data collection sight for the exercise
Analog vs. Digital
. Each student should have a pencil and paper, and a thermometer.
Someone should bring the calibrated string, bell, and timer. Place the grid
over the exact same area as in
Analog vs. Digital
. Place each student in the
exact center of each square or next to any landmark in the square. Have each
student hold the thermometer so that it is in the center of the square and at
90 degrees (perpendicular to the ground. Each thermometer should face the same
direction in relation to the sun so that the difference in data reflects
landscape temperature rather than data collection technique.

Be sure to control the measurements by considering each of the following:

Distance of the thermometer from object to be sensed.

Direction of the thermometer in relation to the sun.

Time when thermometers are read.

Placement of students in the grid.

Wait three minutes and ring the bell. At the sound of the bell, all
students should read their thermometers and record the temperature shown on
paper. (The temperature should be recorded with the best precision possible
with the thermometers, perhaps to a tenth of a degree.) Repeat this procedure
two to four times at three minute intervals.

Collect the materials and return to the classroom. Students can now
average their data or chose a specific, consistent collection to represent each
square of the grid. List or graph the data on the board to get a range.
Calibrate (normalize) the range, then assign colors to each zone. When
assigning colors to each zone, you can use cool colors for lower temperatures
and warm colors for higher temperatures. Refer to the sample of a color scheme
in the figure below.

Any color code can be used, but remember, the purpose of this exercise is for
students to see that objects have properties that can be represented
visually.

Students can now determine the color of their own square then use that
color to color in the square on the large grid. Each student can reduce and
replicate the large grid by coloring corresponding squares on their 20 x 20 cm
grid sheets.

Compare today's image with those created from the
Analog vs. Digital
activity. Can you see any common features? Look at your homemade RSI. Is it
an analog or a digital image? What can you see? What does the image tell you?
How can you use this information? Can you tell which areas have biotic or
abiotic features in them? What is the scale of our large remotely sensed
image? What is the scale of your reduced RSI? What is the resolution of each
image? How can we create an image with greater resolution?

Discuss the relationship between the colors and the electromagnetic
spectrum. What does an RSI in the infrared tell you that other images do not?
What can you tell that you could not tell before?

Assessment:
You work for a county rescue agency. It has rained heavily enough during the
last twenty-four hours to cause extensive flooding. the telephone lines are
down in fifty percent of the county. Your agency needs information on the
locations where the flooding has reached levels that are dangerous for the
citizens. How can an RSI help you? Can an infrared or a visible light image
be of the most help?

Extensions:

Repeat this activity at another time of the day or year. Analyze the
difference between the two or more data sets.

Take a walk around the campus or town and take temperature readings at
various sites. Compare the readings with the school-yard site and discuss.

Change the color code by changing the relationship between colors
(monochromatic, analogous, complimentary) or the calibration within the range
(20-degree range divided by 4 degrees per zone gives 5 colors to use; 20-degree
range divided by 2 degrees per zone gives 10 colors to use.) Have students
fill in a new grid creating a different image.

Create a coordinate grid by using the degrees of temperature to be the
values within the image and the number of the degrees to be the corresponding
integers. Discuss with your students if and how this is different than
assigning number to the values within the image that they have created.